Positron Emission Tomography (PET) using ¹⁸F-FluoroDeoxyGlucose (¹⁸F-FDG), a radiolabelled analogue of the glucose, is used to get an image of the glucose consumption in the body. As most tumor masses show a high glucose consumption, PET is widely used in oncology for diagnosis and patient monitoring. In the context of patient monitoring, the motivation is to decrease the time interval needed to assess treatment (radiotherapy or chemotherapy efficieny) compared to therapeutic follow-up based only on anatomic imaging only (Computed Tomography or Magnetic Resonance Imaging). My research project aimed at proposing and improving quantitative methods in FDG-PET to better characterize tumor evolution.In PET, many factors affect the accuracy of parameters estimated from the images. Among them, Partial Volume Effect (PVE) remains difficult to correct, mainly due to the low spatial resolution of PET images. To determine the impact of PVE on treatment response evaluation, a preliminary study was performed using Monte Carlo simulated PET scans. An additional study was conducted based on the analysis of the PET/CT (Computed Tomography) data of 40 Metastatic Colorectal Cancer (MCC) patients treated with chemotherapy at the Jules Bordet Institute (Brussels, Belgium). The analysis of the 101 tumors showed that criteria such as the Standardized Uptake Value (SUV), which does not include PVE correction, were better predictors of tumors evolutions than PVE corrected criteria. This is because without PVE correction, SUV includes information on both metabolic volume and metabolic activity, which are two relevant pieces of information to characterize the tumor. A second part of our work was to study the potential of tumor texture analysis in patient monitoring, following promising results reported in the literature. Texture analysis was applied to the MMC patients data previously mentioned but did allow to a better segregation of tumors responses as compared to indices currently used in the clinics. We found that this was partly due to the lack of robustness of the textures indices.Finally, we evaluated a Factor Analysis in Medical Images Series (FAMIS) method to characterize tumor evolution during treatment. This study focused on 9 series of 4 to 6 PET/CT scans acquired all along the radiotherapy/radio-chemotherapy of patients treated at the Centre Hospitalier Universitaire Henri Becquerel (Rouen, France). In addition to the rich visual information brought by this method, a quantitative analysis of the results made it possible to characterize response heterogeneity as seen using FAMIS. In particular, FAMIS clearly demonstrated the occurrence of inflammatory processes. In addition, due to the low metabolic activity of the tumors at the end of the treatment, many conventional indices could not describe the tumor changes, while FAMIS gave a full assessment of the tumor change over time.
